Abstract Number:
3309
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Theophilus B.K. Acquah (1), Shafie Khalil (2)
Institutions:
(1) University of Northern Colorado,Department of Applied Statistics and Research Methods, Department of Applied Statistics and Research Methods,Greeley,Co,United States, (2) Department of Applied Statistics & Research Methods, University of Northern Colorado, United States, Greeley, CO
Co-Author:
Shafie Khalil
Department of Applied Statistics & Research Methods, University of Northern Colorado, United States
First Author:
Presenting Author:
Abstract Text:
This research enhances fMRI data analysis by integrating temporal dynamics into spatial random field theory. We developed a new test statistic,, within the time-adaptive Scale Space Gaussian Random Field Model, focusing on signal detection in fMRI data. It captures the global maximum across spatial and temporal dimensions.
Our methodology, employing the Functional Autoregressive (FAR (1)) model, focuses on temporal dependencies and spatial arrangements in data, significantly contributing to neuroimaging studies. We used a simulation approach to estimate the p-value for testing the signal using X_max and understand its advantages in analyzing spatial-temporal patterns in fMRI data.
Keywords:
Time-Adaptive Scale Space|Gaussian Random Field Model|fMRI Data Analysis|Functional Autoregressive Model|Statistical Methodology|
Sponsors:
Section on Statistics in Imaging
Tracks:
fMRI
Can this be considered for alternate subtype?
Yes
Are you interested in volunteering to serve as a session chair?
No
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.
I understand